The DNA damage response (DDR) is a complex signaling network essential for the maintenance of genomic DNA. DNA within a cell is under constant attack from both exogenous and endogenous agents, highlighting the importance of the DDR. The DDR brings together a multitude of cellular pathways to control the fate of a cell following DNA damage, including cell cycle arrest, DNA repair, apoptosis and/or cell cycle re-entry. The objective of the proposed research is to use a systems-based approach to better understand how different kinases are integrated into the canonical DDR response pathways in cancer and how the temporal distribution of kinase activity affects cell fate after DNA damage. In general, this will lead to the identification of important signaling pathways that can be targeted o maximize the efficacy of known anti-cancer chemotherapeutics. The goal of Specific Aim 1 is to design, synthesize, and evaluate a kinase activity sensor for c-Jun N-terminal kinase (JNK), an implicated kinase in the DDR. In Specific Aim 2, the goals are to use the JNK activity sensor, together with a panel of other known kinase activity sensors, to quantify the temporal distribution of kinase activity following DNA damage in cancer cell culture models and to generate a computation model to describe the differential kinase responses following DNA damage. Lastly, the goals of Specific Aim 3 are to evaluate kinase activity in two different mouse models of cancer following DNA damage, to determine appropriate drug combination therapies using the kinase-profiling approach, and to test the drug combination hypothesis in the mouse tumor models. This work will highlight the importance of quantitative systems-based approaches and how these strategies can maximize therapeutic benefit of known therapeutic agents in the treatment of human disease. PUBLIC HEALTH RELEVANCE: The primary objectives of the proposed research are to identify the roles of several kinases in the DNA damage response and identify therapy combinations for the treatment of cancer using information garnered from a quantitative systems-based approach. Ultimately, this research will provide insights into how to maximize the therapeutic benefit of chemotherapeutic agents and/or combinations for the treatment of cancer.